Links
- Author: Ethan Mollick
- Category: rss
- URL: www.oneusefulthing.org/p/against…
- Author: Aravind
- Category: rss
- URL: newsletter.terrawatchspace.com/last-week…
🔗 Against "Brain Damage”
The final quote of “[o]ur fear of AI “damaging our brains” is actually a fear of our own laziness” has a lot of power, although it also oversees the mirrors of “nudges” that technology creates to act lazily.
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ways of using AI to help, rather than hurt, your mind.
If you outsource your thinking to the AI instead of doing the work yourself, then you will miss the opportunity to learn.
the harm happens even when students have good intentions.
we have increasing evidence that, when used with teacher guidance and good prompting based on sound pedagogical principles, AI can greatly improve learning outcomes.
Moving away from asking the AI to help you with homework to helping you learn as a tutor is a useful step.
find more in the Wharton Generative AI Lab prompt library.
while AI is more creative than most individuals, it lacks the diversity that comes from multiple perspectives.
The deeper risk is that AI can actually hurt your ability to think creatively by anchoring you to its suggestions. This happens in two ways.
the anchoring effect. Once you see AI’s ideas, it becomes much harder to think outside those boundaries.
Second, as the MIT study showed, people don’t feel as much ownership in AI generated ideas, meaning that you will disengage
how do you get AI’s benefits without the brain drain? The key is sequencing. Always generate your own ideas before turning to AI.
Every post I write, like this one, I do a full draft entirely without any AI
Only when it is done do I turn to a number of AI models and give it the completed post and ask it to act as a reader: Was this unclear at any point, and how, specifically could I clarify the text for a non-technical reader? And sometime like an editor: I don’t like how this section ends, can you give me 20 versions of endings that might fit better.
there is the option to have it help make us better. One interesting example is using AI as a facilitator.
If you want to keep the human part of your work: think first, write first, meet first.
Our fear of AI “damaging our brains” is actually a fear of our own laziness.
🔗 Last Week in Earth Observation: May 26, 2025
Aravind has a really interesting take on why the hyperscalers are moving into the weather model space.
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I think the real story here is not about weather accuracy, and it is definitely not about replacing ECMWF or NOAA in the future.
This is really about weather becoming part of the cloud infrastructure, about turning forecasting into a cloud-native service that’s deeply embedded within their compute ecosystems.
For sectors such as energy, insurance, agriculture, logistics and finance, weather is not just data, it is a key decision driver. If you can offer native, on-demand, customisable forecasts, users will start building their products and workflows around you: models, simulations, dashboards, alerts and triggers, aka a sticky service layer.
TL;DR: I think Google and Microsoft are trying to make weather foundational by turning it into a programmable infrastructure layer, that powers the horizontal layer of weather intelligence and climate services.
🔗 OSMlanduse a dataset of European Union land use at 10 m resolution derived from OpenStreetMap and Sentinel-2